本文整理汇总了Python中mne.read_events方法的典型用法代码示例。如果您正苦于以下问题:Python mne.read_events方法的具体用法?Python mne.read_events怎么用?Python mne.read_events使用的例子?那么, 这里精选的方法代码示例或许可以为您提供帮助。您也可以进一步了解该方法所在类mne
的用法示例。
在下文中一共展示了mne.read_events方法的4个代码示例,这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞,您的评价将有助于系统推荐出更棒的Python代码示例。
示例1: test_write_does_not_alter_events_inplace
# 需要导入模块: import mne [as 别名]
# 或者: from mne import read_events [as 别名]
def test_write_does_not_alter_events_inplace():
"""Test that writing does not modify the passed events array."""
data_path = testing.data_path()
raw_fname = op.join(data_path, 'MEG', 'sample',
'sample_audvis_trunc_raw.fif')
events_fname = op.join(data_path, 'MEG', 'sample',
'sample_audvis_trunc_raw-eve.fif')
raw = mne.io.read_raw_fif(raw_fname)
events = mne.read_events(events_fname)
events_orig = events.copy()
bids_root = _TempDir()
write_raw_bids(raw=raw, bids_basename=bids_basename, bids_root=bids_root,
events_data=events, overwrite=True)
assert np.array_equal(events, events_orig)
示例2: test_raw_to_mask_pipeline
# 需要导入模块: import mne [as 别名]
# 或者: from mne import read_events [as 别名]
def test_raw_to_mask_pipeline():
# Smoke test for the pipeline MNE.Raw -> raw_to_mask -> Comodulogram
path = mne.datasets.sample.data_path()
raw_fname = path + '/MEG/sample/sample_audvis_filt-0-40_raw.fif'
event_fname = path + ('/MEG/sample/sample_audvis_filt-0-40_raw-eve.fif')
raw = mne.io.read_raw_fif(raw_fname, preload=True)
events = mne.read_events(event_fname)
low_sig, high_sig, mask = raw_to_mask(raw, ixs=(8, 10), events=events,
tmin=-1., tmax=5.)
estimator = Comodulogram(
fs=raw.info['sfreq'], low_fq_range=np.linspace(1, 5, 5),
low_fq_width=2., method='tort', progress_bar=False)
estimator.fit(low_sig, high_sig, mask)
estimator.plot(tight_layout=False)
plt.close('all')
示例3: _calc_epoches
# 需要导入模块: import mne [as 别名]
# 或者: from mne import read_events [as 别名]
def _calc_epoches(params):
subject, events_id, tmin, tmax = params
out_file = op.join(LOCAL_ROOT_DIR, 'epo', '{}_ecr_nTSSS_conflict-epo.fif'.format(subject))
if not op.isfile(out_file):
events = mne.read_events(op.join(REMOTE_ROOT_DIR, 'events', '{}_ecr_nTSSS_conflict-eve.fif'.format(subject)))
raw = mne.io.Raw(op.join(REMOTE_ROOT_DIR, 'raw', '{}_ecr_nTSSS_raw.fif'.format(subject)), preload=False)
picks = mne.pick_types(raw.info, meg=True)
epochs = find_epoches(raw, picks, events, events_id, tmin=tmin, tmax=tmax)
epochs.save(out_file)
else:
epochs = mne.read_epochs(out_file)
return epochs
示例4: _read_events
# 需要导入模块: import mne [as 别名]
# 或者: from mne import read_events [as 别名]
def _read_events(events_data, event_id, raw, ext, verbose=None):
"""Read in events data.
Parameters
----------
events_data : str | array | None
The events file. If a string, a path to the events file. If an array,
the MNE events array (shape n_events, 3). If None, events will be
inferred from the stim channel using `find_events`.
event_id : dict
The event id dict used to create a 'trial_type' column in events.tsv,
mapping a description key to an integer valued event code.
raw : instance of Raw
The data as MNE-Python Raw object.
ext : str
The extension of the original data file.
verbose : bool | str | int | None
If not None, override default verbose level (see :func:`mne.verbose`).
Returns
-------
events : array, shape = (n_events, 3)
The first column contains the event time in samples and the third
column contains the event id. The second column is ignored for now but
typically contains the value of the trigger channel either immediately
before the event or immediately after.
"""
if isinstance(events_data, str):
events = read_events(events_data, verbose=verbose).astype(int)
elif isinstance(events_data, np.ndarray):
if events_data.ndim != 2:
raise ValueError('Events must have two dimensions, '
'found %s' % events_data.ndim)
if events_data.shape[1] != 3:
raise ValueError('Events must have second dimension of length 3, '
'found %s' % events_data.shape[1])
events = events_data
elif 'stim' in raw:
events = find_events(raw, min_duration=0.001, initial_event=True,
verbose=verbose)
elif ext in ['.vhdr', '.set'] and check_version('mne', '0.18'):
events, event_id = events_from_annotations(raw, event_id,
verbose=verbose)
else:
warn('No events found or provided. Please make sure to'
' set channel type using raw.set_channel_types'
' or provide events_data.')
events = None
return events, event_id